{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T04:52:39Z","timestamp":1773031959865,"version":"3.50.1"},"reference-count":41,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,4,12]],"date-time":"2025-04-12T00:00:00Z","timestamp":1744416000000},"content-version":"vor","delay-in-days":101,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004835","name":"Zhejiang University","doi-asserted-by":"publisher","award":["ICT2023B39"],"award-info":[{"award-number":["ICT2023B39"]}],"id":[{"id":"10.13039\/501100004835","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>Inspired by the genetic evolution mechanism of DNA, a hybrid DNA Gray Wolf Optimizer (hDNA\u2010GWO) is proposed to develop an accurate kinetic model. This algorithm incorporates innovative DNA encoding, selection, crossover, and mutation operators inspired by genetic processes. We adopt the roulette\u2010wheel method to select individuals with greater environmental adaptability from the current population to form the next population. The crossover operation involves swapping gene segments between paired chromosomes to create new individuals and maintain the population diversity. The mutation operator can maintain the diversity of the population, avoid the phenomenon of \u201cpremature\u201d convergence, and effectively improve the local search capability. The performance of hDNA\u2010GWO is investigated on typical benchmark functions compared to GWO, PSO, GWO\u2010PSO, and GWO\u2010GA. In addition, the superior search capabilities of our model are validated by kinetic parameter estimation using experimental data from supercritical water oxidation processes. The results indicate that the hDNA\u2010GWO can overcome premature convergence and obtain higher\u2010quality global optimal solutions.<\/jats:p>","DOI":"10.1155\/cplx\/5523778","type":"journal-article","created":{"date-parts":[[2025,4,12]],"date-time":"2025-04-12T03:36:51Z","timestamp":1744429011000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Advanced DNA\u2010Inspired Gray Wolf Algorithm for Kinetic Parameter Estimation in Supercritical Water Oxidation"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2272-2851","authenticated-orcid":false,"given":"Zhenhua","family":"Qin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qilai","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,4,12]]},"reference":[{"key":"e_1_2_12_1_2","unstructured":"LinH. MairalJ. andHarchaouiZ. A Generic Quasi-Newton Algorithm for Faster Gradient-Based Optimization 2017."},{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1080\/02331934.2018.1487423"},{"key":"e_1_2_12_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-10139-6"},{"key":"e_1_2_12_4_2","volume-title":"Differential Evolution\u2014A Practical Approach to Global Optimization [M]","author":"Price K.","year":"2005"},{"key":"e_1_2_12_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11721-007-0002-0"},{"key":"e_1_2_12_6_2","volume-title":"Nature-Inspired Optimization Algorithms","author":"Yang X. S.","year":"2021"},{"key":"e_1_2_12_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2013.12.007"},{"key":"e_1_2_12_8_2","first-page":"108","article-title":"Artificial Bee Colony Algorithm and its Application in Combinatorial Optimization","volume":"1","author":"Zheng W.","year":"2010","journal-title":"Journal of Taiyuan University of Science and Technology"},{"key":"e_1_2_12_9_2","doi-asserted-by":"publisher","DOI":"10.1080\/21642583.2019.1708830"},{"key":"e_1_2_12_10_2","doi-asserted-by":"publisher","DOI":"10.1504\/ijista.2007.011574"},{"key":"e_1_2_12_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04656-1"},{"key":"e_1_2_12_12_2","doi-asserted-by":"publisher","DOI":"10.3390\/su141610246"},{"key":"e_1_2_12_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106751"},{"key":"e_1_2_12_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2009.03.016"},{"key":"e_1_2_12_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2010.03.005"},{"key":"e_1_2_12_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2010.12.036"},{"key":"e_1_2_12_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2012.05.018"},{"key":"e_1_2_12_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2012.03.046"},{"key":"e_1_2_12_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2007.01.012"},{"key":"e_1_2_12_20_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-43546-3"},{"key":"e_1_2_12_21_2","doi-asserted-by":"publisher","DOI":"10.3390\/a9010004"},{"key":"e_1_2_12_22_2","doi-asserted-by":"publisher","DOI":"10.21474\/ijar01\/1132"},{"key":"e_1_2_12_23_2","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/2981282"},{"key":"e_1_2_12_24_2","first-page":"1","article-title":"A Harmonic Estimator Design with Evolutionary Operators Equipped Grey Wolf Optimizer","volume":"145","author":"Akash S.","year":"2020","journal-title":"Expert Systems with Applications"},{"key":"e_1_2_12_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113917"},{"key":"e_1_2_12_26_2","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/2030489"},{"key":"e_1_2_12_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jestch.2017.11.001"},{"key":"e_1_2_12_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2018.06.008"},{"key":"e_1_2_12_29_2","doi-asserted-by":"crossref","unstructured":"BouchairA. YagoubiB. andMakhloufS. A. HS-GWO: A Hybrid Approach for Virtual Network Embedding in SDN-Enabled Distributed Cloud Proceedings of the Future of Information and Communication Conference June 2022 594\u2013610 https:\/\/doi.org\/10.1007\/978-3-030-98015-3_42.","DOI":"10.1007\/978-3-030-98015-3_42"},{"key":"e_1_2_12_30_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01919-x"},{"key":"e_1_2_12_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10140-5"},{"key":"e_1_2_12_32_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40305-021-00341-0"},{"key":"e_1_2_12_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.09.100"},{"key":"e_1_2_12_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cherd.2017.05.008"},{"key":"e_1_2_12_35_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118303"},{"key":"e_1_2_12_36_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.03.041"},{"key":"e_1_2_12_37_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.11.051"},{"key":"e_1_2_12_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2018.12.004"},{"key":"e_1_2_12_39_2","unstructured":"DingY.andRenL. DNA Genetic Algorithm for Design of the Generalized Membership-type Takagi-Sugeno Fuzzy Control System Proceedings of the IEEE International Conference on Systems Man and Cybernetics June 2000 3862\u20133867."},{"key":"e_1_2_12_40_2","first-page":"1589","article-title":"Modeling of Fuzzy Recurrent Neural Networks Based on Chaotic DNA Genetic Algorithm","volume":"28","author":"Chen X.","year":"2011","journal-title":"Control Theory & Applications"},{"key":"e_1_2_12_41_2","doi-asserted-by":"publisher","DOI":"10.1002\/aic.690390117"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/cplx\/5523778","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/cplx\/5523778","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/cplx\/5523778","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T03:55:14Z","timestamp":1773028514000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/cplx\/5523778"}},"subtitle":[],"editor":[{"given":"Dan","family":"Seli\u015fteanu","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["10.1155\/cplx\/5523778"],"URL":"https:\/\/doi.org\/10.1155\/cplx\/5523778","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"value":"1076-2787","type":"print"},{"value":"1099-0526","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"2024-09-11","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-03-13","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"5523778"}}